In neural network the connection strength of each neuron is updated through learning. Through repeated simulations of crisp neural network, we propose the idea that for each neuron in the network, we can obtain reduced model with more efficiency using wavelet based multiresolution analysis (MRA) to form wavelet based quasi fuzzy weight sets (WBQFWS). Such type of WBQFWS provides good initial so...

This paper presents a new fuzzy group decision-making approach by using probabilities and ordered weighted averages (OWA). Thus, we are able to assess the problem considering probabilistic information and the attitudinal character of the decision maker. For doing so, the fuzzy generalized probabilistic OWA (FGPOWA) operator is presented. It is an aggregation operator that unifies the probabilit...

In this paper a new type of fuzzy regularity, viz. fuzzy p∗regularity has been introduced and studied by a newly defined closure operator, viz., fuzzy p∗-closure operator. Also we have found the mutual relationship of this closure operator among other closure operators defined earlier. In p∗-regular space, p∗-closure operator is an idempotent operator. In the last section, p∗-closure operator h...

K-complex is an underlying pattern in the sleep EEG. Due to the role of sleep studies inneurophysiologic and cognitive disorders diagnosis, reliable methods for analysis and detection of this patternare of great importance. In our previous work, Synchrosqueezing Transform (SST) was proposed for analysisof this pattern. SST is an EMD-like tool, which benefits from wavelet transform and reallocat...

The lack of double negation and de Morgan properties makes fuzzy logic unsymmetrical. This is the reason why fuzzy versions of notions like closure operator or Galois connection deserve attention for both antiotone and isotone cases, since they are not dual. This paper offers them attention, comming to the following conclusions: some kind of hardly describable ”local preduality” still makes pos...

In this report, we discuss results of modelling and forecasting nonstationary financial time series using a combination of the maximal overlap discreet wavelet transform (MODWT) and fuzzy logic. A financial time series is decomposed into an over complete, shift invariant wavelet representation. A fuzzy-rule base is created for each individual wavelet sub-series to predict future values. To form...

We present the fuzzy induced generalized OWA (FIGOWA) operator. It is an aggregation operator that uses the main characteristics of the fuzzy OWA (FOWA) operator, the induced OWA (IOWA) operator and the generalized OWA (GOWA) operator. Therefore, it uses uncertain information represented in the form of fuzzy numbers, generalized means and order inducing variables. The main advantage of this ope...

The image data is normally corrupted by additive noise during acquisition. This reduces the accuracy and reliability of any automatic analysis. For this reason, denoising methods are often applied to restore the original image. In proposed method a wavelet shrinkage algorithm based on fuzzy logic and the DT-DWT scheme is used. In particular, intra-scale dependency within wavelet coefficients is...

We develop a new decision making model based on the use of a unified approach between the probability, the weighted average and the ordered weighted averaging (OWA) operator in an uncertain environment that can be assessed with fuzzy numbers (FNs). We present a new aggregation operator called the fuzzy probabilistic ordered weighted averaging – weighted averaging (FPOWAWA) operator. We study it...

The hybrid averaging (HA) is an aggregation operator that uses the weighted average (WA) and the ordered weighted averaging (OWA) operator in the same formulation. In this paper, we introduce several generalizations of the HA operator by using generalized and quasi-arithmetic means, fuzzy numbers and order inducing variables in the reordering step of the aggregation process. We present the fuzz...